Disclosed is a method for calculating an error rate of alarm that reports a failure of facility, calculating a true probability and a false probability of alarms generated for each time zone by a past failure record data and calculating the error rate of the alarm at a rate of the false probability to the true probability of the alarms generated for each time zone.
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1. A method for calculating an error rate of an alarm that reports a failure of a facility, the method comprising: calculating a true probability of alarms generated within a period of time occurring during a day and a false probability of the alarms generated within the period of time occurring during the day based on a past failure record data of the facility; and calculating the error rate of the alarm as a ratio of the false probability of the alarms to the true probability of the alarms generated within the period of time occurring during the day.
A method for calculating the error rate of an alarm that indicates a facility failure. The method involves first calculating the "true probability" of alarms occurring during a specific time period of the day, based on past failure data. It also calculates the "false probability" of alarms during that same period, again using past failure data. The error rate is then determined by dividing the "false probability" by the "true probability" for that time period. This provides a measure of how reliable the alarm is for that specific time.
2. The method of claim 1 , wherein calculating the true probability and the false probability of the alarms comprises: calculating a cumulative distribution function (CDF) of a service life of the facility based on the past failure record data of the facility; and calculating the cumulative distribution function of a lead time based on the past failure record data of the facility.
The method for calculating an error rate of an alarm that reports a failure of a facility, the method comprising: calculating a true probability of alarms generated within a period of time occurring during a day and a false probability of the alarms generated within the period of time occurring during the day based on a past failure record data of the facility; calculates the true and false probabilities by: 1) calculating a Cumulative Distribution Function (CDF) representing the facility's service life, based on past failure records. 2) calculating a CDF representing the "lead time" (time between alarm and failure), also based on past failure records. Both CDFs are derived from historical facility data.
3. The method of claim 2 , wherein calculating the cumulative distribution function of the service life of the facility comprises: sampling a time interval in which a facility inspection is performed, based on service life of the facility, as a plurality of sampled service life data of the facility; and calculating the cumulative distribution function of the service life of the facility based on the plurality of sampled service life data of the facility.
The method of calculating a true and false probability by calculating a cumulative distribution function (CDF) of a service life of the facility based on the past failure record data of the facility, which entails: 1) sampling time intervals when facility inspections occur, based on the facility's service life, to create multiple "sampled service life data points". 2) then, calculate the CDF of the facility's service life based on these sampled data points. This step focuses on statistically modeling the service life using inspection data.
4. The method of claim 3 , wherein calculating the cumulative distribution function of the service life of the facility comprises: configuring a plurality of data groups including the plurality of the service life data, by randomly extracting any number of data among the plurality of sampled facility service life data; calculating a probability that a certain facility service life data is included for each data group; and calculating the cumulative distribution function of the certain facility service life data in the entire plurality of sampled service life data by calculating an average value of the probability.
The method of calculating the cumulative distribution function of the service life of the facility comprises: grouping sampled service life data by randomly extracting a subset of the data points into multiple groups; calculating the probability of a particular service life data point being included in each group; and finally, calculating the CDF for that specific service life data point across all sampled data by averaging the inclusion probabilities across all data groups. This is a bootstrapping technique for estimating the CDF.
5. The method of claim 2 , wherein calculating the cumulative distribution function of the lead time comprises: sampling a difference between a time of occurrence of failure in the past and a time of generation of the alarm; and calculating the cumulative distribution function of the lead time by a difference between the sampled time of occurrence of failure time in the past and the time of generation of the alarm.
The method of calculating a true and false probability by calculating a cumulative distribution function (CDF) of a lead time based on the past failure record data of the facility, entails: sampling the time difference between when a failure occurred in the past and when the alarm was generated. Then, calculate the CDF of the lead time using these sampled time differences. This step aims to statistically model the delay between alarm and actual failure.
6. The method of claim 1 , further comprising: storing a failure record data used to calculate the error rate of the alarm and storing the error rate of the alarm.
The method for calculating an error rate of an alarm that reports a failure of a facility, the method comprising: calculating a true probability of alarms generated within a period of time occurring during a day and a false probability of the alarms generated within the period of time occurring during the day based on a past failure record data of the facility; and calculating the error rate of the alarm as a ratio of the false probability of the alarms to the true probability of the alarms generated within the period of time occurring during the day. The method also includes storing the past failure record data used for error rate calculations, as well as the calculated error rate itself.
7. The method of claim 6 , wherein storing the failure record data comprises: storing a time at which a facility inspection is performed on the facility, an alarm generation time, a failure occurrence time, and a lead time of the alarm generation time.
The method including storing a failure record data used to calculate the error rate of the alarm and storing the error rate of the alarm, specifies that storing the failure record data involves storing the following information: the time when a facility inspection was performed, the time when an alarm was generated, the time when the actual failure occurred, and the lead time (the time difference) between the alarm generation and the failure occurrence.
8. The method of claim 1 , further comprising: when a new alarm is generated, estimating a new error rate calculated by new failure record data corresponding to the failure record data.
The method for calculating an error rate of an alarm that reports a failure of a facility, the method comprising: calculating a true probability of alarms generated within a period of time occurring during a day and a false probability of the alarms generated within the period of time occurring during the day based on a past failure record data of the facility; and calculating the error rate of the alarm as a ratio of the false probability of the alarms to the true probability of the alarms generated within the period of time occurring during the day. It further involves estimating a new error rate using updated (new) failure record data whenever a new alarm is generated.
9. The method of claim 8 , further comprising: providing the new alarm to a user if the new error rate of the new alarm is less than a preset threshold value.
The method of estimating a new error rate calculated by new failure record data corresponding to the failure record data, in response to generation of the new alarm. It then provides the new alarm information to a user only if the newly calculated error rate is below a predetermined acceptable threshold. This acts as a filter, prioritizing alarms with lower error rates for user attention.
10. An apparatus for calculating an error rate of an alarm that reports an occurrence of failure of a facility, the apparatus comprising: a memory configured to store a past failure record data of the facility; a bootstrap estimation unit configured to calculate a true probability of alarms generated within a period of time occurring during a day and a false probability of the alarms generated within the period of time occurring during a day based on the past failure record data of the facility; and an error rate calculation unit configured to calculate the error rate of the alarm as a ratio of the false probability of the alarms to the true probability of the alarms generated within the period of time occurring during the day.
An apparatus calculates the error rate of a facility failure alarm. It includes a memory to store past failure records. A "bootstrap estimation unit" calculates the "true" and "false" probabilities of alarms during specific times of day based on the stored failure data. An "error rate calculation unit" then divides the "false" probability by the "true" probability to determine the alarm's error rate.
11. The apparatus of claim 10 , wherein the bootstrap estimation unit is further configured to calculate a cumulative distribution function (CDF) of a service life of the facility, and a cumulative distribution function of a lead time, based on the past failure record data of the facility.
The apparatus calculating the error rate of a facility failure alarm that includes a memory to store past failure records, a "bootstrap estimation unit" that calculates the "true" and "false" probabilities of alarms during specific times of day based on the stored failure data, and an "error rate calculation unit" that then divides the "false" probability by the "true" probability to determine the alarm's error rate. The bootstrap estimation unit also calculates a Cumulative Distribution Function (CDF) representing the facility's service life and a CDF representing the lead time (time between alarm and failure), both based on past failure records.
12. The apparatus of claim 11 , wherein the bootstrap estimation unit is further configured to sample a time interval of a facility inspection based on the service life of the facility, as a plurality of sampled service life data of the facility, and calculate the cumulative distribution function of the facility service life based on the plurality of sampled service life data of the facility.
The apparatus including a bootstrap estimation unit that also calculates a Cumulative Distribution Function (CDF) representing the facility's service life and a CDF representing the lead time (time between alarm and failure), both based on past failure records, operates by: sampling time intervals related to facility inspections and the service life to collect "sampled service life data." The CDF of the facility service life is then calculated based on these sampled data points.
13. The apparatus of claim 12 , wherein the bootstrap estimation unit is further configured to configure a plurality of data groups including the plurality of the service life data, by randomly extracting any number of data among the plurality of sampled facility service life data, calculate a probability that a certain facility service life data is included for each data group, and calculate the cumulative distribution function of the certain facility service life data in the entire plurality of sampled service life data by calculating an average value of the probability.
The apparatus including a bootstrap estimation unit that also calculates a Cumulative Distribution Function (CDF) representing the facility's service life and a CDF representing the lead time (time between alarm and failure), both based on past failure records, operates by: creating multiple data groups containing subsets of the sampled service life data (by random extraction). Then, for each group, the probability of a certain service life data being included is calculated. Finally, it averages these probabilities across all groups to estimate the CDF for that specific service life data.
14. The apparatus of claim 11 , wherein the bootstrap estimation unit is further configured to sample a difference between a time of occurrence of failure in the past and a time of generation of the alarm, and calculate the cumulative distribution function of the lead time by a difference between the sampled time of failure occurrence of failure time in the past and the time of generation of the alarm.
The apparatus including a bootstrap estimation unit that also calculates a Cumulative Distribution Function (CDF) representing the facility's service life and a CDF representing the lead time (time between alarm and failure), both based on past failure records, operates by: sampling the time difference between a past failure and its corresponding alarm to determine the "lead time." The CDF of the lead time is then calculated using these sampled time differences.
15. The apparatus of claim 10 , wherein the memory is further configured to store: a failure record data used to calculate the error rate of the alarm; and the error rate of the alarm.
An apparatus calculates the error rate of a facility failure alarm. It includes a memory to store past failure records and the calculated error rate. A "bootstrap estimation unit" calculates the "true" and "false" probabilities of alarms during specific times of day based on the stored failure data. An "error rate calculation unit" then divides the "false" probability by the "true" probability to determine the alarm's error rate.
16. The apparatus of claim 15 , wherein the failure record data is at least one of a time of performance of facility inspection on the facility, an alarm generation time, a failure occurrence time, and a lead time of the alarm generation time.
The apparatus including a memory to store past failure records and the calculated error rate, stores failure record data which includes at least one of the following: the time of facility inspection, the time the alarm was generated, the time of the failure occurrence, and the lead time between alarm and failure.
17. The apparatus of claim 10 , further comprising: a selection unit configured to estimate a new error rate calculated by new failure record data corresponding to the failure record data, in response to generation of the new alarm.
An apparatus calculates the error rate of a facility failure alarm. It includes a memory to store past failure records. A "bootstrap estimation unit" calculates the "true" and "false" probabilities of alarms during specific times of day based on the stored failure data. An "error rate calculation unit" then divides the "false" probability by the "true" probability to determine the alarm's error rate. It further includes a selection unit which, upon generation of a new alarm, estimates a new error rate based on updated failure records.
18. The apparatus of claim 17 , further comprising: an alarm generation unit configured to provide the new alarm to a user if the new error rate of the new alarm is less than a preset threshold value.
The apparatus calculating the error rate of a facility failure alarm that includes a memory to store past failure records, a "bootstrap estimation unit" that calculates the "true" and "false" probabilities of alarms during specific times of day based on the stored failure data, an "error rate calculation unit" that then divides the "false" probability by the "true" probability to determine the alarm's error rate, and a selection unit which, upon generation of a new alarm, estimates a new error rate based on updated failure records. It also includes an alarm generation unit, which provides the new alarm to a user only if the new error rate is below a preset threshold value.
19. An apparatus for calculating an error rate of an alarm that reports a failure of a facility, the apparatus comprising: at least one processor; a memory configured to load a computer program executed by the processors; and a storage configured to store a computer program that manages a license, wherein the computer program comprises a set of instructions which are executable by the at least one processor to: calculate a true probability of alarms generated and a false probability of alarms generated within a period of time occurring during a day and a false probability of the alarms generated within the period of time occurring during a day based on a past failure record data; and calculate the error rate of the alarm as a ratio of the false probability to the true probability of the alarms generated within the period of time occurring during the day.
An apparatus calculates the error rate of a facility failure alarm. It contains at least one processor, memory to load a program for execution, and storage for the program. The program, when executed by the processor(s), calculates a "true probability" and "false probability" of alarms during a period of time based on past failure records, and then calculates the error rate by dividing the false probability by the true probability.
20. A non-transitory computer-readable recording medium having embodied thereon a computer program, which when executed by a computer causes the computer to execute a method for calculating an error rate of an alarm that reports a failure of a facility, the method comprising: calculating a true probability of alarms generated within a period of time occurring during a day and a false probability of the alarms generated within the period of time occurring during the day based on a past failure record data of the facility; and calculating the error rate of the alarm as a ratio of the false probability of the alarms to the true probability of the alarms generated within the period of time occurring during the day.
A non-transitory computer-readable medium stores a program that, when executed, calculates the error rate of a facility failure alarm. The program calculates a "true probability" and "false probability" of alarms during a period of time based on past failure records. The error rate is then calculated by dividing the false probability by the true probability.
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April 5, 2016
July 11, 2017
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